A Fuzzy Cognitive Mapping Approach to the Conference Selection Problem

[1]  Husam Jasim Mohammed,et al.  The effects of perceived conference quality on attendees’ behavioural intentions , 2020 .

[2]  Jose L. Salmeron,et al.  Benchmarking main activation functions in fuzzy cognitive maps , 2009, Expert Syst. Appl..

[3]  K. Chon,et al.  Convention participation decision-making process. , 1997 .

[4]  Abdollah Amirkhani,et al.  A review of fuzzy cognitive maps in medicine: Taxonomy, methods, and applications , 2017, Comput. Methods Programs Biomed..

[5]  Jose L. Salmeron,et al.  Augmented fuzzy cognitive maps for modelling LMS critical success factors , 2009, Knowl. Based Syst..

[6]  Dae-kwan Kim,et al.  Destination-selection attributes for international association meetings: A mixed-methods study , 2019, Journal of Destination Marketing & Management.

[7]  Osonde Osoba,et al.  Fuzzy cognitive maps of public support for insurgency and terrorism , 2017 .

[8]  Dohee Kim,et al.  An Exploratory Study of Local Organizations' Conference Choice Factors , 2010 .

[9]  J. Mair,et al.  The UK association conference attendance decision-making process , 2009 .

[10]  Youcheng Wang,et al.  Examining the motivation, perceived performance, and behavioral intentions of convention attendees: evidence from a regional conference. , 2007 .

[11]  Wei-Wen Wu,et al.  Developing global managers' competencies using the fuzzy DEMATEL method , 2007, Expert Syst. Appl..

[12]  Koen Vanhoof,et al.  Deterministic learning of hybrid Fuzzy Cognitive Maps and network reduction approaches , 2020, Neural Networks.

[13]  Colin Eden,et al.  Analyzing cognitive maps to help structure issues or problems , 2004, Eur. J. Oper. Res..

[14]  Koen Vanhoof,et al.  A review on methods and software for fuzzy cognitive maps , 2019, Artificial Intelligence Review.

[15]  Luis C. Ortigueira,et al.  Innovation in Tourist Management through Critical Success Factors: A Fuzzy Map , 2012 .

[16]  M. Oppermann.  Convention destination images: analysis of association meeting planners' perceptions , 1996 .

[17]  Marcy Mintz,et al.  An approach to conference selection and evaluation: advice to avoid “predatory” conferences , 2018, Scientometrics.

[18]  章 勇刚.  Construction and Empirical Study of Evaluation System of International Convention & Exhibition Related Tourism Site Selection—An Analysis Based on AHP , 2019 .

[19]  Witold Pedrycz,et al.  Genetic learning of fuzzy cognitive maps , 2005, Fuzzy Sets Syst..

[20]  Karl Perusich,et al.  Using fuzzy cognitive maps to identify multiple causes in troubleshooting systems , 2008, Integr. Comput. Aided Eng..

[21]  J. Mair,et al.  Academic conferences: a female duo-ethnography , 2018 .

[22]  Effects of Destination Image on Meeting Participation Intentions: Empirical Findings from a Professional Association and its Annual Convention , 2007 .

[23]  Venkatesh,et al.  A Longitudinal Field Investigation of Gender Differences in Individual Technology Adoption Decision-Making Processes. , 2000, Organizational behavior and human decision processes.

[24]  Erhan Bozdag,et al.  A new approach to DEMATEL based on interval-valued hesitant fuzzy sets , 2018, Appl. Soft Comput..

[25]  Andrew Wirth,et al.  Measuring Differences Between Cognitive Maps , 1992 .

[26]  Jose L. Salmeron,et al.  Dynamic risks modelling in ERP maintenance projects with FCM , 2014, Inf. Sci..

[27]  W. Kim,et al.  The Analysis of Seoul as an International Convention Destination , 2004 .

[28]  Chrysostomos D. Stylios,et al.  Fuzzy Cognitive Maps , 2008 .

[29]  József Mezei,et al.  Aggregating expert knowledge for the measurement of systemic risk , 2016, Decis. Support Syst..

[30]  Adil Baykasoğlu,et al.  Comprehensive fuzzy FMEA model: a case study of ERP implementation risks , 2017, Operational Research.

[31]  Miguel A. Márquez,et al.  What determines the holding of association meetings in a global context? , 2019, Journal of Travel & Tourism Marketing.

[32]  Bart Kosko,et al.  Fuzzy Cognitive Maps , 1986, Int. J. Man Mach. Stud..

[33]  I PapageorgiouElpiniki,et al.  A review of fuzzy cognitive maps in medicine , 2017 .

[34]  J. Mair,et al.  The motives and barriers of association conference attendance: Evidence from an Australasian tourism and hospitality academic conference , 2018 .

[35]  Julie Whitfield,et al.  Contemporary factors influencing association conference attendance , 2020 .

[36]  J. Louviere,et al.  The Determinants of Convention Site Selection: A Logistic Choice Model from Experimental Data , 2004 .

[37]  Wei Zhang,et al.  Applying Importance-Performance Analysis to Beijing as an International Meeting Destination , 1997 .

[38]  D. Chavis,et al.  Sense of community: A definition and theory , 1986 .

[39]  Amit Konar,et al.  Reasoning and unsupervised learning in a fuzzy cognitive map , 2005, Inf. Sci..

[40]  G. Chiappa,et al.  International convention tourism: A choice modelling experiment of host city competition , 2019, Tourism Management.

[41]  S. Suh,et al.  The Competitiveness of International Meeting Destinations in Asia , 2005 .

[42]  Ching-Fu Chen.  Applying the Analytical Hierarchy Process (AHP) Approach to Convention Site Selection , 2006 .

[43]  C. Eden.  ON THE NATURE OF COGNITIVE MAPS , 1992 .

[44]  Elpiniki I. Papageorgiou,et al.  An integrated breast cancer risk assessment and management model based on fuzzy cognitive maps , 2015, Comput. Methods Programs Biomed..

[45]  Bongkosh Ngamsom Mhm,et al.  A Pilot Study of Motivations, Inhibitors, and Facilitators of Association Members in Attending International Conferences , 2000 .

[46]  Karagöz Deniz Yüncü,et al.  Türk akademisyenlerin kongre tercihleri üzerine bir araştırma , 2010 .

[47]  M. Deery,et al.  Relationships and Factors Influencing Convention Decision-Making , 2005 .

[48]  H. Chacko,et al.  Determining the importance of US convention destination attributes , 2000 .

[49]  J. Beck,et al.  Understanding Motivations, Inhibitors, and Facilitators of Association Members in Attending International Conferences , 2001 .

[50]  Taha Mansouri,et al.  Learning Fuzzy Cognitive Maps with modified asexual reproduction optimisation algorithm , 2019, Knowl. Based Syst..

[51]  Jos De Roo,et al.  Diagnosis Support System based on clinical guidelines: comparison between Case-Based Fuzzy Cognitive Maps and Bayesian Networks , 2014, Comput. Methods Programs Biomed..

[52]  M. Bevilacqua,et al.  Fuzzy cognitive maps for adverse drug event risk management , 2018 .

[53]  M.F.A.M. van Maarseveen,et al.  Generalised fuzzy cognitive maps: Considering the time dynamics between a cause and an effect , 2020, Appl. Soft Comput..

[54]  Koen Vanhoof,et al.  On the convergence of sigmoid Fuzzy Cognitive Maps , 2016, Inf. Sci..

[55]  Vanja Pavluković,et al.  Factors affecting conference participation decision-making , 2020, Journal of the Geographical Institute Jovan Cvijic, SASA.

[56]  Athanasios K. Tsadiras,et al.  Comparing the inference capabilities of binary, trivalent and sigmoid fuzzy cognitive maps , 2008, Inf. Sci..

[57]  Namho Chung,et al.  The Threats of North Korea’s Missile and Visitors’ International Conference Choice Behavior , 2019, Sustainability.

[58]  Joanne Yoo,et al.  Revisiting Determinants of Convention Participation Decision Making , 2010 .

[59]  Tamer Eren,et al.  Selection of Academic Conferences Based on Analytical Network Processes , 2016 .

[60]  Maurizio Bevilacqua,et al.  A Fuzzy Cognitive Maps Tool for Developing a RBI&M Model , 2016, Qual. Reliab. Eng. Int..

[61]  Abdollah Amirkhani,et al.  A Novel Fuzzy Inference Approach: Neuro-fuzzy Cognitive Map , 2019, International Journal of Fuzzy Systems.

[62]  Nick Bassiliades,et al.  RuleML representation and simulation of Fuzzy Cognitive Maps , 2013, Expert Syst. Appl..

[63]  Hailin Qu,et al.  A refined model of factors affecting convention participation decision-making , 2007 .

[64]  J. Mair,et al.  Exploring intentions to attend a convention: a gender perspective , 2013 .